The Wow Factor Preconceptions and Expectations for Data Analysis Software in Qualitative Research
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
10.1177/0894439303262625
MacMillan,
SOCIAL SCIENCE
Koenig /COMPUTER
THE WOW FACTOR
REVIEW ARTICLE
The Wow Factor
Preconceptions and Expectations for
Data Analysis Software in Qualitative Research
KATIE MACMILLAN
THOMAS KOENIG
Loughborough University
Discussions on computer-assisted qualitative data analysis software often begin with the assumption
that research will automatically be improved through the use of such software. Consequently, reviews
frequently focus on practical concerns with the various software packages. Rather than theoretical con-
siderations of its suitability to the method of analysis, such descriptions frequently treat software as the
method of analysis. The following article calls for a clearer understanding of the role of software within
research, with critical evaluation focusing on the methodological issues surrounding software use, as
well on its technological innovations. The authors examine a number of factors that foster a tendency
toward uncritical appraisal—including unrealistic expectations of the software as a methodology in
itself; the treatment of qualitative analysis as a single, homogenized category; and the use of grounded
theory as a legitimating link between tool and method.
Keywords: qualitative research; theory; grounded theory; CAQDAS; computer
T he following article is based on an overview of the literature on qualitative computer
software programs and the expectations encouraged by many such reviews. We exam-
ine a number of the factors that contribute to assumptions that the software is adequate as a
method of analysis in itself, and the implications that these beliefs have for the research envi-
ronment as a whole. Our overall aim is to stimulate debate on issues seldom discussed at
length in this area, and in doing so make a number of (perhaps) controversial suggestions
about why this might be so, and what can be done to encourage a more lively appraisal of
computer software use in qualitative research.
Our 2-year research project1 is in the process of investigating methods for the analysis of
media content. This includes evaluating the contradictions and compatibilities between vari-
ous approaches, and involves, among other considerations, examining the main qualitative
computer software programs,2 and the value of these as methodological tools to assist differ-
ent methods of analysis within the social sciences.
Although the social science research environment in general cultivates a dynamic climate
in which the analytical assessment of theories and methods of research abound, very few
articles discuss the use of computer-assisted qualitative data analysis software (CAQDAS)
in their studies, and those that do so are remarkably uncritical in their appraisals (Weaver &
Atkinson, 1995). In an examination of the Sociological Abstracts database, we found only
31 references to either Nud*ist, Atlas.ti, NVivo, winMAX, Kwalitan, MAXqda, Qualrus, or
Hyperresearch since 1990, compared to 220 references to SPSS, SAS, and Stata. Seven of
Social Science Computer Review, Vol. 22 No. 2, Summer 2004 179-186
DOI: 10.1177/0894439303262625
© 2004 Sage Publications
179180 SOCIAL SCIENCE COMPUTER REVIEW
these articles were not primarily concerned with CAQDAS, with the other 24 discussing
advantages and disadvantages of the software. Ten of these articles were written by develop-
ers themselves. In contrast, the majority of abstracts mentioning statistical packages focused
on substantive research.
Lyn Richards (2002, p .263) explored possible reasons why, despite a widespread adop-
tion of qualitative computing, there is little debate over the software’s “methodological inno-
vations.” Because developers tend to focus on the technological capabilities of the software,
researchers with little understanding of social science methodology take it for granted that
whatever work is needed to legitimate a methodological tool has already been done. This can
create an often uncritical allegiance to CAQDAS (Thompson, 2002; also see Bong, 2002),
with “the very name of the computer program” seen as “sufficient in itself to justify the way
the data are analyzed ” (Thompson, 2002, para. 7.41).
The following discussion proposes that, to stimulate critical debate within the area, the
wow factor of CAQDAS needs to be deconstructed, with its contribution to research de-
mystified and clarified. What we term the wow factor is an unrealistically high level of
expectation about CAQDAS use. These beliefs are reinforced in a number of ways, including
reviews that herald the software programs as the only way forward for qualitative research.
This, linked with the researcher’s basic uncertainty over what the software can and cannot do
(Crowley, Harré, & Tagg, 2002), the complexity of the software program, the time and the
difficulty involved in learning how to operate it (see Thompson, 2002), and the confusing use
of program-specific technical language in descriptions of the software’s various functions
contribute to a climate in which the researcher can be misled into thinking of CAQDAS as
more than a methodological tool. The wow factor is reflected in an assumption that the soft-
ware is the methodology, and that by simply learning to operate the program, the researcher
is doing analysis.
CAQDAS
For those involved in the development and promotion of computer software, the issue is
not whether to use CAQDAS, but how it should be used. Developers see their work as crucial
to the social sciences and promote it as such. In his guide to qualitative data analysis for
social scientists, Ian Dey (1993, p. xi), the author of Hypersoft, stated that the “days of scis-
sors and paste are over” for researchers; QSR’s Lyn Richards (1995, p. 105) declared that
“all researchers working in the qualitative mode will be clearly helped by some computer
software.” Those involved in CAQDAS training also treat it as a prerequisite; for example,
CAQDAS trainer Diógenes Carvajal (2002, p. 1) asserted that “almost everybody” now uses
computer software, and that “today, the use of software to assist qualitative analysis is a
must.”
For researchers considering how qualitative data analysis software might transform the
analytical process, and looking for a balance of views in the literature, serious critiques are
thin on the ground. Most discussions on CAQDAS begin with the assumption that any
research will be enhanced by using computer software in qualitative analysis (also see
Bourdon, 2002; Buston, 1997; Smith & Hesse-Biber, 1996). Many of these texts are practi-
cal guides aimed at helping researchers to choose the right package and showing how various
functions are employed in data management. As mentioned, a number of authors discuss
their own software (also see Muhr, 2000; Seidel, Kjolseth, & Seymour, 1988), whereas oth-
ers provide descriptive reviews of the most popular software packages (e.g., Alexa & Zuell,
1999; Weitzman & Miles, 1995). Individual articles often consist of a summary of one or
more programs (e.g., Barry, 1998; DeNardo & Levers, 2002; Wikander, 2000) or a detailedMacMillan, Koenig / THE WOW FACTOR 181
account of using CAQDAS within an individual project (Bong, 2002; Bourdon, 2002;
Buston, 1997).
Although such reviews may be useful, an overabundance of practical descriptions on how
to operate the qualitative software preempt first-stage discussions on whether it is appropri-
ate to use it at all and do little to encourage debate over anything but the utility of functions.
QUALITATIVE ANALYSIS
Because of the mystique surrounding CAQDAS (Crowley et al., 2002), perpetuated by a
constant flow of new, updated, and “improved” software programs (Barry, 1998, para. 3.1),
there is understandable confusion among researchers about what the software can do and the
extent to which its functions constitute analysis. Indeed, there is a misconception among
some researchers that analysis is achieved simply by organizing the data into hierarchical
categories within the software program (Carvajal, 2002; Crowley et al., 2002; Thompson,
2002). This misunderstanding can be the result both of a lack of knowledge on the part of the
researcher about research methods in general and lack of precision in literature that describes
the software as analytical.
According to Nigel Fielding (2000, p. 9), many researchers using CAQDAS have little
training in social science methods. Quoting an earlier estimate from the CAQDAS Network-
ing Project (see Fielding & Lee, 2000), Fielding stated that 15% to 20% of participants
involved in software training programs are nonacademics with little or no social science
background. For users with less experience of the diversity of qualitative methods, texts
describing CAQDAS as a method can perpetuate misunderstandings about the extent to
which software functions produce analysis. Giving the widely cited handbook by Denzin
and Lincoln (1994) as his example, Fielding (2000) argued that
contemporary methodological literature could even be taken as suggesting that academic social
scientists regard qualitative software as a separate kind of analysis [emphasis added]. (p. 6)
For the author, this characterization is unsatisfactory “both because it exaggerates the
coherence of a field which actually provides a variety of types of computer support for quali-
tative data analysis and because it confuses a technical resource with an analytic approach”
(Fielding, 2000, p. 6).
The social sciences are well served with literature on qualitative methods (e.g., Bannister,
Burman, Parker, Taylor, & Tindall, 1994; Coffey & Atkinson, 1996; Denzin & Lincoln,
1994), as well as a number of good texts on the use of computers in qualitative data analy-
sis (Dey, 1993; Fielding & Lee, 1991; Tesch, 1990), most of which attend to the variety of
methods within qualitative analysis. As Bannister et al. (1994) reminded us,
there is no single qualitative method, and quite different aims will be accomplished by different
interpretative approaches. (p. 3)
Despite this, however, there is a tendency within descriptive accounts of the value of
CAQDAS to gloss over what is meant by the term qualitative. There is an assumption within
projects using computer software programs that at least one of the packages reviewed will
help any qualitative study, with, in many cases, qualitative analysis treated as a kind of
homogenized, ideal-type version of research (see Coffey, Holbrook, & Atkinson, 1996).
Although, of course, many qualitative methods are clearly not homogenous, posing different
theoretical questions and operating within different theoretical frameworks, as a vague182 SOCIAL SCIENCE COMPUTER REVIEW
description, qualitative analysis becomes the polar opposite of quantitative analysis (e.g.,
Bourdon, 2002), with the “furthering of analysis” (p. 18) reliant on the researcher’s knowl-
edge of the scope of the software program.
In a very general way, this is how it might seem it should be, with analysis enhanced by the
abilities of the researcher to work well within the chosen discipline. However, we can see
how such descriptions also create the impression that analysis is actually done by the soft-
ware. Here, the wow factor kicks in—rather than emphasizing that CAQDAS is a tool for
organizing data (Coffey et al., 1996; Gilbert, 2002; Kelle, 1997), not a method of analysis,
this view implies that the better the researcher is at working the program, the better the
analysis.
Not only do many studies treat qualitative analysis as a consolidated single method, some
(e.g., Bazeley, 2002) argue for a fusion of qualitative and quantitative analyses. Such de-
scriptions effectively package quantitative and qualitative methods as two not dissimilar
categories—one that turns data into statistics and the other that turns data into descriptive
codes. Not only are the methodologies treated as but two research methods, one qualita-
tive and the other quantitative, the boundaries are further blurred by suggesting that these
methods—traditionally viewed as approaching the world from a very different set of under-
standings (Roberts & Wilson, 2002)—are compatible enough to be mixed together.
This theoretical vagueness, in which qualitative and quantitative methods are mixed
together and used on an ad hoc basis, enables CAQDAS to be placed within the category of
qualitative analysis, while extolling the virtues of a kind of quali-quanti analysis.
GROUNDED THEORY
Such descriptions often avoid assessing the software for its suitability as a tool from a par-
ticular theoretical perspective. Theory, if mentioned at all, will more often than not involve a
brief description of grounded theory, particularly in comparison to descriptions of the opera-
tional functions of the software.
Controversially, although not implausibly, Jörg Strübing (2002, p. 319) suggested that
researchers who cannot present a good, clear methodological framework tend to “legiti-
mize” their findings by mentioning grounded theory. Some pay lip service to the method but
then go on to admit that their study departs from its theoretical framework. Sylvain Bourdon
(2002, p. 17), for example, situated his study within grounded theory but then admitted that
his own method of analysis is more of a “broad sorting” of data than the kind of analysis more
usually set out within this approach.
In an overview of the literature connecting CAQDAS to method, we examined the
archives of QUAL-software, a mailing list that is dedicated to the discussion of CAQDAS.3
All archived postings, as well as all web pages that were referenced in these postings, were
downloaded, yielding a total of 9,284 documents. These files were subsequently searched
for the occurrence of keywords associated with certain qualitative methods (discourse analy-
sis, ethnography, frame analysis, and grounded theory); an approach intersecting qualitative
and quantitative methodology (network analysis); and a quantitative method (regression
analysis). To see whether a certain methodology is under- or overrepresented in a CAQDAS
research, we compared frequency counts to the same keyword search results for all post-
1989 journal articles in the Sociological Abstracts database (see Table 1).
The findings unanimously show that grounded theory is the dominant methodology for
CAQDAS users—who mention it on average 30 times more frequently than sociologists as a
whole. Discourse analysis and frame analysis are less frequent in CAQDAS research than inMacMillan, Koenig / THE WOW FACTOR 183
TABLE 1
Results of Examination of QUAL-software Archives and Sociological Abstracts Database
QUAL Softwarea Sociological Abstracts
b
Keyword n % n % Ratio
Grounded theory 380 4.09 228 0.14 29.94
Network analysis 95 1.02 770 0.46 2.22
Discourse analysis 79 0.85 1,812 1.09 0.78
c
Ethnograph$ 186 2.00 4,566 2.74 0.73
Frame analysis 1 0.01 172 0.10 0.10
Regression analysis 3 0.03 1,378 0.83 0.04
NOTE: • X 52 = 2,384, significant at the p < .0001 level.
a. Comprising 9,284 files.
b. Comprising 167,757 records.
c. The $ sign is a placeholder for any letter character, such as in “ethnography” or “ethnographic.” We
added this condition to filter for hits on the Ethnograph software.
sociological research in general, with grounded theory mentioned 300 times more fre-
quently than frame analysis.
Grounded theory is, however, an ambiguous methodology, which, with its tendency
toward positivism,4 can further confuse the theory with the methodological tool for the
CAQDAS user. Although it is now a deeply internally divided discipline (Strübing, 2002,
p. 320), according to its proponents, this methodology treats theory as derived from a pro-
cess of comparisons, from, for example, interview data, conversations, observation, and
even surveys (Glaser, 2002; Glaser & Strauss, 1967; Strauss & Corbin, 1990, 1997). Al-
though there are no initial hypotheses, the researcher is engaged in a continuous search for
evidence to disprove the research findings and to support the final conclusions. However,
unlike a number of other qualitative methods, the analysis is not structured by the method but
comes out of a process of coding, conceptualization, and categorization (Allan, 2003).
It should be emphasized that other qualitative methodologies and epistemologies caution
precisely against such research practices. For example, in ethnography, it is commonplace to
warn against “going native” (e.g., Hammersley & Atkinson 1983, p. 100), and most con-
structionism, not to mention deconstructionism, discourages the emergence of theoretical
concept from data (e.g., Luhmann, 1990, p. 20)—as does critical theory, which regards
inductive theorizing as an anathema (Habermas, 1963/1989). Glaser (2002, p. 7) is aware of
these approaches and argued that grounded theory does not require “personal distance for
accuracy” because it “automatically . . . transcends the descriptive data.”
The argument here, however, is not whether the reviewer’s subsequent analysis faithfully
resides within the remits of grounded theory, or any other theoretical framework, but rather
that such descriptions—the initial location of the new-kid software program within the old-
boy tradition of an established theoretical method—work to legitimate the study as qualita-
tive research and the subsequent sorting and coding as qualitative analysis.
A further legitimation lies within descriptions of the software functions as “theory build-
ing” (see Lonkila, 1995; Richards & Richards, 1991, 1994). The term evokes an image
of an active process, rather than a mechanical function, from which, as with grounded the-
ory, theory will emerge. Implicated in such descriptions is the notion that theory is some-
thing that develops alongside the analysis rather than the traditional expectation within184 SOCIAL SCIENCE COMPUTER REVIEW
qualita tive analysis that analysis is guided by specific theoretical underpinnings (MacMillan
& McLachlan, 1999).
Rather than clarifying the role of software programs, the promotion of a theory-building
function, and a discursive link with the tenets of grounded theory, contributes to the myth
that qualitative software, in conjunction with grounded theory, is a method of analysis in
itself.
A tendency toward epistemological positivism provides conditions for further misunder-
standings around the software’s capabilities by substituting methodological rigor for de-
scriptions of a particular aspect of the research process. Rigor is treated not as the product of
concise conceptual thought, ideas, and examination of research materials within a particular
research framework but as something provided by a software tool able to produce replicable
data sets.
CONCLUSION
As we have shown, misunderstandings exist, not only in software use but also in descrip-
tions of qualitative analysis, with little attention paid to different research methods. By ques-
tioning grounded theory as representative of qualitative methods, and by examining the ten-
dency to link it with CAQDAS, we aim to stimulate CAQDAS users into considering the
method of analysis before the software tool and before the research process begins.
There are concerns among developers themselves about misunderstandings and misuse
of software programs in qualitative analysis, and a general agreement that problems do
occur. Some developers encourage caution in promoting software use, whereas others see
education and better training as the main solution (see Carvajal, 2002; Dey, 1993; Richards,
1995).
There is, however, clearly a need for more than practical training. Reviews that continue
to focus on discussions between developers of software programs and their followers, rather
than addressing “the higher literature of methods” (Richards, 2002, pp. 265-266), stifle
debate. To encourage the critical assessment of CAQDAS use within qualitative analysis, the
software should be reviewed within the epistemological framework of the qualitative
research method chosen to suit the study. This reasserts the role of theory in research, in
which research questions are defined not by the software tool but by the problems to be
examined.
NOTES
1. The Assessment and Development of New Methods for the Analysis of Media Content project
(www.lboro.ac.uk/research/mmethods/; award no. H333250014) is funded by the ESRC Research Methods
Programme.
2. Our evaluation includes Atlas.ti, Concordance, Ethnograph, Maxqda, Nvivo, N6, Qualrus, and Textquest.
3. From www.jiscmail.ac.uk/lists/qual-software.html, accessed November 4, 2003.
4. We refer here to an epistemological positivism, which prescribes the emergence of theory from data and
excludes prior theorizing.
REFERENCES
Alexa, A., & Zuell, C. (1999). A review of software for text analysis. Mannheim, Germany: ZUMA.
Allan, G. (2003). A critique of using grounded theory as a research method. Electronic Journal of Business Research
Method, 2(1), 1-10.
Bannister, P., Burman, E., Parker, I., Taylor, M., & Tindall, C. (1994). Qualitative methods in psychology: A research
guide. Buckingham, UK: Open University Press.MacMillan, Koenig / THE WOW FACTOR 185
Barry, C. A. (1998). Choosing qualitative data analysis software: Atlas/ti and Nud*ist compared. Sociological
Research Online, 3(3). Retrieved from www.socresonline.org.uk/socresonline/3/3/4.html
Bazeley, P. (2002). The evolution of a project involving an integrated analysis of structured qualitative and quantita-
tive data: From N3 to Nvivo. International Journal of Social Research Methodology, 5(3), 229-243.
Bazeley, P., & Richards, L. (2000). The NVivo qualitative project book. London: Sage.
Bong, S. A. (2002). Debunking myths in qualitative data analysis. Forum Qualitative Sozialforschung, 3(2).
Retrieved from www.qualitative-research.net/fqs-texte/2-02/2-02bong-e.htm
Bourdon, S. (2002). The integration of qualitative data analysis software in research strategies: Resistances and pos-
sibilities. Forum Qualitative Sozialforschung, 3(2). Retrieved from www.qualitative-research.
net/fqs-texte/2-02/2-02bourdon-e.htm
Buston, K. (1997). NUD*ist in action: Its use and its usefulness in a study of chronic illness in young people. Social
Research Online, 2(3). Retrieved from www.socresonline.org.uk/socresonline/2/3/6.html
Carvajal, D. (2002). The artisan’s tools. Critical issues when teaching and learning CAQDAS. Forum Qualitative
Sozialforschung, 3(2). Retrieved www.qualitative-research.net/fqs-texte/2-02/2-
02carvajal-e.htm
Coffey, A., & Atkinson, P. (1996). Making sense of qualitative data analysis: Complementary strategies. Thousand
Oaks, CA: Sage.
Coffey, A., Holbrook, B., & Atkinson, P. (1996). Qualitative data analysis: Technologies and representations. Socio-
logical Research Online, 1(1). Retrieved from www.socresonline.org.uk/socresonline/1/1/
4.html
Crowley, C., Harré, R., & Tagg, C. (2002). Qualitative research and computing: Methodological issues and practices
in using QSR NVivo and Nud*ist. International Journal of Social Research Methodology, 5(3), 193–197.
DeNardo, A. M., & Levers, L. L. (2002, June). Using NVivo to analyze qualitative data. Paper presented at the 14th
Annual Ethnographic and Qualitative Research in Education Conference, Duquesne University. Retrieved from
http://www.education.duq.edu/leaders/EQRE/papers2002/DeNardo&Levers.pdf
Denzin, N. K., & Lincoln, Y. S. (1994.). Handbook of qualitative research. Thousand Oaks, CA: Sage.
Dey, I. (1993). Qualitative data analysis: A user-friendly guide. London: Routledge.
Fielding, N. (2000). The shared fate of two innovations in qualitative methodology: The relationship of qualitative
software and secondary analysis of archived qualitative data. Forum Qualitative Sozialforschung, 1(3). Re-
trieved from http://qualitative-research.net/fqs-texte/3-00/3-00fielding-e.
htm
Fielding, N., & Lee, R. M. (2000). Patterns and potentials in the adoption of qualitative software: The implications of
user experiences and software training. Proceedings of the Fifth International Conference on Social Science
Methodology. Retrieved from http://qualitative-research.net/fqs-texte/3-00/3-00
fielding-e.htm
Fielding, N. G., & Lee, R. M. (Eds.). (1991). Using computers in qualitative research. Thousand Oaks, CA: Sage.
Gilbert, L. S. (2002). Going the distance: “Closeness” in qualitative data analysis software. International Journal of
Social Research Methodology, 5(3), 215-228.
Glaser, B. (2002). Conceptualization: On theory and theorizing using grounded theory. International Journal of
Qualitative Methods, 1(2). Retrieved from www.ualberta.ca/~ijqm.
Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Chi-
cago: Aldine.
Habermas, J. (1963/1989). Analytische Wissenschaftstheorie und Dialektik: Ein Nachtrag zur Kontroverse-
zwischen Popper und Adorno [Analytical science theory and dialectics: a supplement to the Popper and Adorno
controversy]. In T. W. Adorno, R. Dahrendorf, J. Habermas, H. Pilot, & K. R. Popper (Eds.), Der Positiv-
ismusstreit in der deutschen Soziologie (pp. 155-191). 1989. Darmstadt, Germany: Luchterhand Literaturverlag.
(Original work published in 1963)
Hammersley, M., & Atkinson, P. (1983). Ethnography, principles in practice. London: Tavistock.
Kelle, U. (1997). Theory building in qualitative research and computer programs for the management of textual data.
Sociological Research Online 2(2). Retrieved from www.socresonline.org.uk/socresonline/2/
2/1.html
Lonkila, M. (1995). Grounded theory as an emerging paradigm for computer-assisted qualitative data analysis. In U.
Kelle (Ed.), Computer-aided qualitative data analysis. London: Sage.
Luhmann, N. (1990). Soziologische Aufklärung: 5. Konstruktivistische Perspektiven [Sociological clarification: 5.
Constuctionist perspective]. Opladen, Germany: Westdeutscher Verlag.
MacMillan, K., & McLachlan, S. (1999). Theory-building with Nud*ist: Using computer assisted qualitative analy-
sis in a media case study. Sociological Research Online, 4(2). Retrieved from www.socresonline.org.
uk/4/2/macmillan_mclachlan.html186 SOCIAL SCIENCE COMPUTER REVIEW
Muhr, T. (2000). Increasing the reusability of qualitative data with XML. Forum Qualitative Sozialforschung, 1(3).
Retrieved from www.qualitative-research.net/fqs-texte/3-00/3-00muhr-e.htm
Richards, T. (2002). An intellectual history of Nud*ist and NVivo. International Journal of Social Research Meth-
odology, 5(3), 199–214.
Richards, L. (1995). Transition work! Reflections on a three-year Nud.ist project. In R. C. Burgess (Ed.), Studies in
qualitative methodology (Vol. 5). Greenwich, CT: JAI.
Richards, T. J., & Richards, L. (1991). The transformation of qualitative method: Computational paradigms and
research processes. In N. G. Fielding & R. M. Lee (Eds.), Using computers in qualitative research. London:
Sage.
Richards, T. J., & Richards, L. (1994). Using computers in qualitative research. In N. D. Denzin & Y. S. Lincoln
(Eds.), Handbook of qualitative research. London: Sage.
Roberts, K. A., & Wilson, R. W. (2002). ICT and the research process: Issues around the compatibility of technology
with qualitative data analysis. Forum Qualitative Sozialforschung, 3(2). Retrieved from www.qualitative-
research.net/fqs-texte/2-02/2-02robertswilson-e.htm
Seidel, J., Kjolseth, R., & Seymour, E. (1988). The ethnograph: A user’s guide. Littleton, CO: Qualis Research
Associates.
Smith, B. A., & Hesse-Biber, S. (1996). Users’experiences with qualitative data analysis software: Neither Franken-
stein’s monster nor muse. Social Science Computer Review, 14(4), 423-432.
Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques.
Newbury Park, CA: Sage.
Strauss, A., & Corbin, J. (Eds.). (1997). Grounded theory in practice. Thousand Oaks, CA: Sage.
Strübing, J. (2002). Just do it? Zum Konzept der Herstellung und Sicherung von Qualität in grounded theory-
basierten Forschungsarbeiten [For the production and protection of quality in grounded theory-based research
projects]. Kölner Zeitschrift für Soziologie und Sozialpsychologie, 54(2), 318-342.
Tesch, R. (1990). Qualitative research: Analysis types and software tools. London: Falmer.
Thompson, R. (2002). Reporting the results of computer-assisted analysis of qualitative research data. Forum Quali-
tative Sozialforschung, 3(2). Retrieved from www.qualitative-research.net/fqs-texte/2-
02/2-02thompson-e.htm
Weaver, A., & Atkinson, P. (1995). From coding to hypertext. In R. G. Burgess (Ed.), Computing and qualitative
research: Studies in qualitative methodology (5th ed., pp. 141-168). Greenwich CT: JAI.
Weitzman, E. A., & Miles, M. B. (1995). Computer programs for qualitative data analysis: A software sourcebook.
Thousand Oaks, CA: Sage.
Wikander, K. (2000). Concordance and diction: Comparative review. Computers & Texts, (18/19), 35-37.
Katie MacMillan is a research associate at Loughborough University, currently examining methods of ana-
lyzing media content. Her long-term research interests include knowledge construction, therapy, and the
application of discourse analysis to talk and texts. She may be reached by e-mail at k.macmillan@
lboro.ac.uk.
Thomas Koenig is a research associate at Loughborough University, working on the above project. His inter-
ests are mainly in quantitative methodology, but also in frame analysis, with substantive interest in social
movements, and collective behavior. He may be reached by e-mail at t.koenig@lboro.ac.uk.You can also read
